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Publication Number: FHWA-RD-01-166
Date: November 2003

Structural Factors for Flexible Pavements—Initial Evaluation of The SPS-1 Experiment Final Report

EXPERIMENT ASSESSMENT—DATA AVAILABILITY AND COMPLETENESS

This chapter presents a summary of the SPS-1 experimental data and summarizes the level E data in the IMS based on the LTPP data collection guidelines at the time of the SPS-1 experimental review. Appendix A provides a brief discussion and summary of each SPS-1 project, including a review of the construction difficulties and project deviations from the experimental plan.

As stated in chapter 1, the IMS is a very dynamic database that is continually updated and revised as new data are entered and checked for anomalies. Figure 2 is a generalized flow chart showing the movement of data and the data quality checks through LTPP. This flow chart is useful for understanding why some of the key data that have been collected for a specific test section do not appear as Level E data in the LTPP database.

LTPP DATA QUALITY CONTROL CHECKS

The quality of the data is the most important factor in any type of analysis. From the outset of the LTPP program, data quality has been considered of paramount concern. Procedures for collecting and processing data were defined and modified as necessary to ensure consistency across various reporting contractors, laboratories, equipment operators, or others. Although these procedures formed the foundation of quality control/quality assurance (QC/QA) and data integrity, many more components of a QC/QA plan were necessary to ensure that the data sent to researchers were as error-free as practical.

LTPP has developed and implemented an extensive QC program that classifies each of the data elements into categories depending upon the location of the data in this QC process. Several components comprise the overall QC/QA plan used on the LTPP data as discussed below.

 

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When the QC/QA programs are completed, the regional engineers review the output and resolve any data errors. Often the data entered are legitimate and accurate, but do not pass a QC/QA check. If this occurs, the regional engineer can document that the data have been confirmed using a comments table in the IMS and can manually upgrade the record to Level E.

Figure 2 shows the movement of data elements and quality checks completed on the data prior to release to the public. Only a fraction of the data fields are checked. A value of A is assigned automatically to a record on entry in the database. A value of B indicates the QC process was executed and a Level C check failed. Any record for which correct section information is stored in the database is available after the QC is completed. A record of the QC processing is included with the record. Since the checks are run in sequence A-E, the last successful check is identified on the record as the record status variable.  A value of B or C indicates that a necessary data element was not available when the QC was processed and does not necessarily imply that the higher level QC was unsuccessful.

There are numerous reasons why some data may be unavailable from the publicly released IMS database at the time the data were actually collected.  Following are some examples:

Therefore, the missing data identified in this report do not necessarily mean that the data were not collected or submitted by the States.  There are several places where data may be delayed and not reach Level E.  The results in this report are based only upon Level E because it was impossible to know the specific reasons why that data did not pass all of the QC checks.  Many of the reasons that prevent data from reaching Level E status are not the result of poor quality or unreliability of the data.  The LTPP program is embarking on a systemwide effort to resolve all unavailable data so that future researchers can access them.

DATA ELEMENT CATEGORIES

All of the data elements included in the SPS-1 experiment were reviewed for their availability and completeness in the LTPP database as listed in table 5.  The data elements were divided into three categories for the review process—essential, explanatory, and informational.  Each category is defined briefly below.

 Although the review of the SPS-1 experiment included all data elements, the detailed review concentrated on those elements that were identified as essential and explanatory.  The key data elements that were evaluated and assessed for determining the quality level and completeness for each project were subdivided into the following types of data, and are discussed in this chapter:

Table 5.  Summary of SPS-1 data elements and their importance to experimental expectations.

Module ID

Data Element

*Data Avail., %

Data Importance

Essential

Explanatory

Informational

 Automated Weather Station
(AWS)

 Daily Max Temp

83

   

X

 Daily Min Tem

   

X

 Daily Mean Temp

   

X

 Maximum Avg Monthly Humidity

   

X

 Minimum Avg Monthly Humidity

   

X

 Monthly Precipitation

X

   

 Number of Days with Precipitation

   

X

 Number of Days with Intense Precipitation

   

X

 Avg Daily Mean Solar Radiation by Month

 

X

 

 Mean Monthly Temp

   

X

 Avg Min Monthly Temp

 

X

 

 Avg Min Monthly Temp

 

X

 

 Days >32 ºC

 

X

 

 Days <0 ºC

 

X

 

 Freeze Index

X

   

 Number of Freeze-Thaw Cycles

 

X

 

 Mean by Month of Avg Daily Wind Speed

   

X

 Climatic
 (CLM)

 Maximum Avg Annual Humidity

89

   

X

 Minimum Avg Annual Humidity

   

X

 Annual Precipitation

X

   

 Number of Days with Intense Precipitation

   

X

 Number of Days with Precipitation

   

X

 Annual Snowfall

   

X

 Number of Days with Snowfall

   

X

 Mean Annual Temp

   

X

 Avg Max Annual Temp

   

X

 Avg Min Annual Temp

   

X

 Max Annual Temp

 

X

 

 Min Annual Temp

 

X

 

 Day >32 °C

 

X

 

 Days <0 °C

 

X

 

 Freeze Index

X

   

 Annual Number of Freeze-Thaw Cycles

 

X

 

 Mean Wind Speed

   

X

 Maintenance
 (MNT)

 Crack Sealing

0

   

X

 Patching

6

   

X

 Asphalt Seal

6

   

X

 Monitoring
 (MON)

 Deflections

100

X

   

 Temp at Testing

94

X

   

 Backcalculated Modulus

X

   

 Manual Distress

100

X

   

 PASCO Distress

50

X

   

 Friction

38

   

X

 Longitudinal Profile

100

X

   

 Transverse Profile

89

X

   

 Construction

 Layer Thickness

94

X

   

 Rod and Level Thickness

78

 

X

 

 Asphalt Grade

72

   

X

 Aggregate Type

67

   

X

 Specific Gravity of Aggregate

56

   

X

 Compaction of the Asphalt

78

   

X

 Laydown Temp

72

   

X

 In Situ Density of Bound Layers

33

 

X

 

 Mix Design Air Voids

67

 

X

 

 Mix Design Asphalt Content

67

 

X

 

 Design VMA

67

 

X

 

 Design Effective Asphalt Content

89

 

X

 

 Marshall Stability

39

   

X

 Marshall Flow

39

   

X

 Hveem Stability

11

   

X

 Hveem Cohesiometer

0

   

X

 Haul Distance

83

   

X

 Plant Type

89

   

X

 Paver Type

89

   

X

 Laydown Width

83

   

X

 Lift Thickness

89

   

X

 Subgrade Stabilization

39

 

X

 

 Location

100

   

X

 Functional Class

100

   

X

 Elevation

100

   

X

 Cost

22

   

X

 Drainage Type

78

X

   

 Shoulder Type

78

   

X

 Traffic
(TRF)

 Estimated ESALs

22

   

X

 Estimated AADT

22

   

X

 W4 Tables

50

X

   

 Monitored AVC

50

X

   

 Monitored AADT

17

 

X

 

 Monitored ESALs

39

X

   

 [Materials]
 Testing
 (TST)

 Core Examination

85

X

   

 Bulk Specific Gravity

67

X

   

 Max Specific Gravity

65

X

   

 Asphalt Content

67

 

X

 

 Moisture Susceptibility

44

 

X

 

 Asphalt Resilient Modulus

0

 

X

 

 Ash Content of AC

44

   

X

 Penetration

67

   

X

 Asphalt Specific Gravity

67

   

X

 Viscosity

67

 

X

 

 Aggregate Specific Gravity

67

   

X

 Aggregate Gradation

67

 

X

 

 Fine Aggregate Particle Shape

39

   

X

 In Situ Density

83

 

X

 

 Layer Thickness

67

X

   

 Treated Base Type

17

 

X

 

 Treated Base Compressive Strength

0

   

X

 Unbound Base Gradation

67

X

   

 Unbound Base Classification

67

X

   

 Unbound Compressive Strength of the Subgrade

33

   

X

 Unbound Base Permeability

39

 

X

 

 Unbound Base Optimum Moisture

67

 

X

 

 Unbound Base Max Density

67

 

X

 

 Unbound Base Modulus

17

 

X

 

 Unbound Base Moisture Content

50

   

X

 Subgrade Gradation

72

X

   

 Subgrade Hydrometer Analysis

78

X

   

 Subgrade Classification

78

X

   

 Subgrade Permeability

33

 

X

 

 Atterberg Limits

78

X

   

 Subgrade Max Density

83

 

X

 

 Subgrade Modulus

83

X

   

 Subgrade Moisture Content

72

   

X

 *Data Availability—percentage of SPS-1 required testing for which data generally are available in the database at Level E.

GENERAL SITE INFORMATION

This assessment includes the site identification and location, key equipment installed at the site, the construction report’s availability, and important dates associated with each of the SPS-1 projects.  The information for this review was obtained from the site construction report, deviation report, or from the IMS tables entitled EXPERIMENT_SECTION and SPS_ID.  All of the site level records for the 18 constructed SPS-1 projects are at Level E.  These data records are complete, as noted in the project summary records presented in appendix A.  Table 6 includes a summary of the site information and report availability for each of the projects.

Construction and deviation reports were available for review from all of the projects except Michigan, Wisconsin, and Montana.  Montana and Wisconsin are new projects, while the Michigan project is 4 years old.  The construction report for the Montana project has been drafted, but is awaiting additional construction information before submittal to LTPP and the Wisconsin construction report was submitted to LTPP after the review had been completed.

AWS equipment has been installed at all sites.  However, WIM and Automated Vehicle Classification (AVC) equipment has not been installed at five of the project sites: Alabama, Delaware, Louisiana, Oklahoma, and New Mexico (see table 6).  This is considered significant to the experiment, especially when trying to validate the more sophisticated mechanistic-empirical design-analysis procedures.  Specifically, reliable and site-specific traffic data are considered vital to National Cooperative Highway Research Program (NCHRP) Project 1-37A, development of the 2002 Guide for the Design of New and Rehabilitated Pavement Structures.

 Table 6. SPS-1 project site information and report availability.

Project

Region

Age, Years

Equipment Installed

Report Availability

AWS

WIM

AVC

Construction

Deviation

Delaware

NA

3.2

X

   

X

X

Virginia

3.7

X

X

X

X

X

Iowa

NC

7.0

X

X

X (5)

X

X

Kansas

5.8

X

X

X

X

X

Nebraska

4.1

X

X

X

X

X

Michigan

4.0

X

X

X

 

X

Ohio

4.6

X

 

X (4)

X

X

Wisconsin

1.8

X (3)

X (3)

X (3)

X (3)

X

Alabama

S

6.4

X

   

X

X

Arkansas

5.7

X

X

X

X

X

Florida

3.7

X

X

X

X

X

Louisiana

2.1

X

   

X

X

New Mexico

3.7

X

   

X

X

Oklahoma

2.1

X

   

X

X

Texas

2.3

X

X (6)

X (6)

X

X

Arizona

W

6.0

X

X

X

X

X

Montana

0.8

X

X (2)

 

X (2)

X

Nevada

4.0

X (1)

X

X

X

X

Notes: 

  1. The AWS for the Nevada project is linked to test sections 320100 and 320200 that are back-to-back.
  2. The Montana project has had a WIM system installed, but the data is on hold pending installation of the new traffic processing software.  The construction report for the Montana project is in draft form and is awaiting additional construction information.
  3. The construction report for the Wisconsin project was submitted to LTPP after the review had been completed. In addition, AWS, WIM and AVC equipment have been installed recently, but no Level E data are available in the IMS.
  4. AVC data were submitted for the Ohio project in 1998, but were not at Level E in the January 2000 release of the database.
  5. AVC data were submitted for the Iowa project in 1993 and 1996, but are not at Level E.
  6. Traffic data have been collected for the Texas project, but those data are not included in the IMS.

DESIGN VERSUS ACTUAL CONSTRUCTION REVIEW

Chapter 3 presented a summary of the construction and specification requirements for each of the SPS-1 projects.  Additionally, the Nomination Guidelines (11) and Construction Guidelines (12) for FHWA’s Guidelines for Nomination and Evaluation of Candidate Projects for Experiment SPS-1 Strategic Study of Structural Factors for Flexible Pavements also established specific site selection criteria and key variable construction guidelines.  The guidelines presented in both of these reports were developed to control quality and integrity of the SPS-1 experiment results and findings.  Therefore, they should be considered in the construction adequacy evaluation and assessment.

One of the main objectives of this study was to identify any confounding factors introduced into the SPS-1 experiment regarding construction deviations or other factors not accounted for in the original experiment design. It is extremely important to evaluate the types of variables that are considered key design factors in the SPS-1 experiment and to determine if any deviation of the design parameters established for the design factorial will adversely affect the experimental expectations.

This section of the report evaluates the design versus the actual construction of key variables identified within the experimental factorial and the above-mentioned experiment guidelines.

Subgrade Soil

The type of subgrade soil is a key factor in the experimental design.  Specifically, the SPS-1 experimental design called for half of the projects to be constructed on coarse-grained soils and the other half to be built over fine-grained soils.  An additional requirement of the experiment was that all test sections at a site be constructed on the same type of soil (i.e., the same soil classification).  Table 7 provides a summary of the subgrade soils and their classification in comparison to the original nomination (refer to table 1).  As tabulated, only one of the sites (Texas) is now listed within a different experimental cell because the subgrade soils were found to be different than originally nominated.

Similarly, the subgrade soils on which these projects were built are relatively consistent for each of the core test sections at a site.  In fact, there are only two projects where the subgrade classification varies between the different test sections at a project—Kansas and New Mexico.  The test sections with the different soil classifications are noted in table 7 and show that 5 of the 18 test sections in Kansas are classified as coarse-grained subgrades, while only 1 of the 12 test sections in New Mexico is classified as coarse-grained.  This subgrade variation is considered typical, and it is not believed that this deviation from the experiment requirement will have a detrimental impact in achieving the expectations of the SPS-1 experiment.

One major discrepancy was noted during the review process.  All subgrades are classified by the RCO and this classification is entered into the SPS1_LAYER table, as shown in table 7. In some cases, this classification is different from the soil type identified on table TST_L05B.  For example, Kansas, Nevada, and Texas have different classifications between tables TST_L05B and SPS1_LAYER.  Thus, an additional check should be added to cross-reference the subgrade soil classification between the TST_L05B and SPS1_LAYER tables to ensure that the same data elements are consistent.

Climate

The SPS-1 experimental design called for each project to be located in one of four different climates: wet-freeze, wet-no-freeze, dry-freeze, or dry-no-freeze. The main purpose of this factor was to obtain SPS-1 projects in different climates, as well as a geographical distribution across the United States and Canada.  Figure 1 provided a summary of the geographical distribution of these projects across the United States and Canada.  Table 8 tabulates the average annual rainfall, mean annual air temperatures, and freezing index that have been measured, which define each site’s climatic zone.

Table 7.  SPS-1 subgrade classification.

State Nominated Soil Type From TST L05B From SPS1_LAYER table
Soil Type
No. Sections Class, OK?
AL
Fine
Silty Clay
15
X
Silty Clay
AZ
Coarse
Well-Graded Sand with Silt and Gravel
3
X
Silty Sand
Silty Sand with Gravel
7
Clayey Sand with Gravel
1
Well-Graded Gravel with Silt and Sand
5
AK
Coarse
Clayey Sand
12
X
Clayey Sand
DE
Coarse
Poorly Graded Sand
14
X
Silty Sand
FL
Coarse
Silty Sand with Gravel
9
X
Poorly Graded Sand
Poorly Graded Sand with Silt and Gravel
4
X
IA
Fine
Clay
1
X
Sandy Clay
Clay with Gravel
8
Clay with Sand
2
Lean Clay with Sand
1
Silty Clay
1
KS
Fine
Clay with Sand
7
X
Sandy Silt
Sandy Clay
4
Silty Clay
2
Sand
1
Silty Sand
4
LA
Fine
Clay
12
X
Silty Clay
MI
Fine
Sandy Clay
13
X
 
MT
Coarse
Poorly Graded Sand with Silt
12
X
Silty Sand
NE
Fine
Silty Clay
12
X
Silty Clay Silt
NV
Coarse
Silty Sand
66
X
Silty
Clayey Sand
NM
Fine
Lean Inorganic Clay
1
X
Clay, Liquid limit > 50
Fat Inorganic Clay
4
Lean Clay with Sand
2
Fat Clay with Sand
1
Sandy Lean Clay
1
Sandy Fat Clay
2
Clayey Sand
1
OH
Fine
Silty Clay
13
X
Silty Clay
OK
Fine
Sandy Clay
13
X
Sandy Clay
TX
Coarse
Sandy Silt
20
NO
Silty Sand
VA
Fine
Fat Clay with Gravel
3
X
Silty Clay
Silty Clay with Sand
1
Gravelly Silty Clay
1
Sandy Silty Clay with Gravel
5
Silt
1
Sandy Silt with Gravel
2
WI
Coarse
 
X
Silty Sand

 


 Table 8.  Summary of key factor values for the SPS-1 projects.

Climate

Subgrade Soil

Project ID

Type of Subgrade Soil

Average Annual Rainfall, mm

Mean Annual Air Temp. °C

Freeze Index °C-Day

Age, Years

AWS, Days

WIM, Days

Estimated KESALs, Year

Wet-Freeze

Fine-Grained

IA

Clay

982

10.8

235

7.0

815

108

130

MI

Sandy Clay

870

8.6

283

4.0

670

250

?

OH

Silty Clay

972

10.1

207

4.6

1,600

0(1)

?

VA

Silty Clay

1,142

14.1

38

3.7

1,299

313

?

Coarse-Grained

DE

Poorly Graded Sand

1,145

13.3

58

3.2

1,200

0

203

WI

Silty Sand

?

?

?

1.8

0(2)

0

?

Wet-No-Freeze

Fine-Grained

AL

Silty Clay

1,340

17.3

9

6.4

1,394

0

237

LA

Clay

1,538

12.9

2

2.1

300

0

524

Coarse-Grained

AR

Clayey Sand

1,224

15.6

47

5.7

1,100

89

170

FL

Silty Sand

1,325

23

0

3.7

800

342

1,463

Dry-Freeze

Fine-Grained

KS

Clay

627

12.9

136

5.8

1,000

232

?

NE

Silty Clay

785

11

228

4.1

1,024

531

119

Coarse-Grained

MT

Poorly Graded Sand

317

7.6

200

0.8

370

0(3)

?

NV

Clayey Sand

223

9.7

156

4.0

0(4)

338

799

Dry-No-Freeze

Fine-Grained

NM

Clay

290

15.4

5

3.7

1,075

0

393

OK

Sandy Clay

869

15.9

45

2.1

400

0

280

TX

Sandy Silt

561

23.3

1

2.3

187

0

10

Coarse-Grained

AZ

Silty Sand

241

18.3

1

6.0

1,480

1,588

185

Notes:      
  1. 278 WIM days were submitted for the Ohio project in 1998, but data are not available for review.
  2. AWS equipment is installed at the site, but no data are available in the January 2000 IMS.
  3. See Montana note 2 at the bottom of table 6.
  4. AWS for the Nevada project is linked to test sections 320100 and 320200.

The general climatic data include actual measurements from at least one nearby weather station for each LTPP site. In addition, a site-specific statistical estimate, based on as many as five nearby weather stations, is available for each project.  These estimates are called virtual weather stations.  The IMS contains monthly and average annual summary statistics.  Daily data for both the virtual weather stations and actual weather stations are kept off-line.  General environmental data available in the IMS are derived from weather data originally collected from the NOAA.

AWS equipment is installed at every SPS-1 project site (refer to table 6). The AWS provides site-specific information for the same parameters as the general environmental tables, but these data are available with monthly, daily, or hourly statistics.  The number of days from the AWS at each project site is summarized in table 8.  An appreciable amount of climatic data has been collected from the AWS.

The SPS-1 project sites include a wide range of freezing index, temperatures, and annual rainfall, as originally planned.  Those sites with an average annual rainfall greater than 1,000 mm are classified as wet and those sites with less than 1,000 mm are classified as dry.  Similarly, the sites with a freezing index greater than 60 ºC-days would be classified as a freezing climate and those with less than 60 ºC-days would be designated as a no-freeze climate. It should be noted that the values used to determine the specific climatic cell assignment are arbitrary and only used to ensure that the projects cover a diverse range of climates.  An annual rainfall of 1,000 mm was used in some of the earlier LTPP studies, while an annual rainfall of 508 mm is used in the latest version of DATAPAVE® for designating the site as wet or dry.  A freezing index value of 60 °C-days was used to determine whether the site falls into a no-freeze or freeze cell while a different value is used in DATAPAVE.

Using these definitions, some sites do not appear to be in the correct experimental cells.  For example, Iowa, Michigan, and Ohio all have average annual rainfalls less than 1,000 mm, but are in the experimental cells designated as a wet climate. It is expected that the average rainfall at the project sites will increase with time.  Similarly, Virginia was originally nominated for a freezing climate but has an average freezing index of 38 °C-days since construction. It is expected that the average freezing index at this site will increase over time.

All sites are in compliance with the appropriate cell requirements based on the NOAA and historical data.  As a result, the climate designations have not been changed on the basis of a few years’ worth of data.  These relatively small differences in the average rainfall and freezing index are not considered detrimental to achieving the SPS-1 experimental objectives or expectations.  The experimental sites still represent a diverse range of climates across the United States and Canada, as originally planned.

Layer Thickness/Structure

The pavement structure data are divided into two elements—layer data and design features. Important general design features such as drainage, lane width, and shoulder type are included in table SPS_GENERAL.  All of the key design feature data are available for all of the SPS-1 test sections, and all are at Level E.

The pavement layer data for the SPS-1 test sections are available from two different sources.  These two sources include the rod and level measurements (IMS Table SPS1_LAYER) and thicknesses from the cores recovered on-site (IMS Table TST_L05B).  Both of these tables were examined to evaluate the thickness measurements and variation of the layer thickness data for each of the structural layers within the SPS-1 cross-sections.  The average thickness of each layer is provided in appendix B for all of the projects for which data are available.  The TST_L05B table contains records for all layers for 17 of the 18 projects.  Layer information on Wisconsin has yet to become available because this project is new and the data have not undergone the QC process. 

The SPS1_LAYER table contains all layer data for the 14 SPS-1 projects that are at Level E.  The projects from which construction data do not exist are Wisconsin, Michigan, Montana, and Nebraska. The Montana and Wisconsin projects are relatively new; the data have been collected, but have not passed the entire QC process

In general, the average layer thicknesses for each layer were as originally planned within the construction guidelines for the SPS-1 experiment.  The one construction element that was not satisfied included the layer thickness deviations from the planned thickness within the experiment. On every test section and project, the variation of the layer thicknesses was greater than the maximum value identified in the construction guidelines (refer to chapter 3). It is believed that the construction guidelines called for a tolerance that was impractical.

Histograms for each layer type and thickness level were prepared to review the distribution of layer thicknesses for all projects.  Examples of these histograms are included in figures 3 through 10.  Each figure includes the distribution of layer thicknesses as included in table TST_ L05B and from the construction data or table SPS1_LAYER.  As shown, the distributions between the different thickness methods are very similar, and the average values from those thickness determination methods are approximately equal.  These thickness variations (or histograms) represent typical construction practices, and all data sets are normally distributed (with the possible exception of the thin [102-mm] DGAB layer).  This variation of layer thickness, which is greater than required by the construction guidelines, is not believed to be a detriment to the experiment or to prevent the experimental objectives from being met.  None of the thickness data sets for the same material overlap (e.g., 102 mm versus 178 mm for the HMA layers).

The pavement cross-section and material types planned for each test section within the core experiment of each project were generally met and adhered to based on the construction guidelines.  The only deviation to the planned cross-sections was for the Iowa project, where a DGAB layer was placed beneath the PATB layer on one of the test sections.  This is not believed to have a significant effect on the experiment.

MATERIALS TESTING

Field and laboratory tests were conducted to establish the properties of each material included in the SPS-1 experiment.  The material properties and the variation of those properties, both between and within the test sections, are required to evaluate and explain causes of performance differences between the test sections.  Many of these properties or material characteristics are those that are currently used in existing pavement design and analysis methods.

The material sampling and testing requirements are documented in the SPS-1 materials sampling and testing guidelines report.(4)  This report contains the development of the SPS-1 sampling and testing plans, field material sampling and testing requirements, and laboratory materials testing requirements for each SPS-1 project site.  SPS-1 materials sampling and testing plans for the subgrade and base materials are provided in chapter 3. In addition, the testing requirements for each of the materials are designated in appendix A.

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Figure 3.   Thickness histograms for the thin HMA layer (102 mm) from  tables SPS1_LAYER (construction data) and TST_L05B.


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Figure 4.  Thickness histograms for the thick HMA layer (178 mm) from tables SPS1_LAYER (construction data) and TST_L05B.


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Figure 5.   Thickness histograms for the thin ATB layer (102 mm) from tables SPS1_LAYER (construction data) and TST_L05B.
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Figure 6.    Thickness histograms for the thick ATB layer (203 mm) from tables SPS1_LAYER (construction data) and TST_L05B.

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Figure 7.  Thickness histograms for the PATB layer from tables  SPS1_LAYER (construction data) and TST_L05B.



  Click to View Alternative Text

Figure 8.  Thickness histograms for the 102-mm DGAB layer from tables
 SPS1_LAYER (construction data) and TST_L05B.

 

Click to View Alternative Text
 
Figure 9.  Thickness histograms for the 203-mm DGAB layer from tables
SPS1_LAYER (construction data) and TST_L05B.


  Click to View Alternative Text

Figure 10. Thickness histograms for the 305-mm DGAB layer from tables
SPS1_LAYER (construction data) and TST_L05B.

Tables 9 through 13 summarize the available test data from selected tests by material type for each of the projects while table 14 provides a summary of the overall materials testing completed for the core test sections.  As shown, there is still a substantial amount of testing that needs to be completed to fill the experiment, even for those data elements or material properties identified as essential (refer to table 5). If this testing is not completed (at least for the essential data elements), the missing laboratory test results from most of the SPS-1 projects will have a detrimental impact on the experiment for achieving the experimental objectives and expectations.

To evaluate the relative difference in construction or the in-place properties, histograms of different material properties were prepared.  Figures 11 through 13 show the variation of air voids in the different HMA and ATB layers.  As shown, these variations are substantial enough to cause a significant difference in performance. In fact, some of the air voids are greater than 10 percent, which indicates inadequate compaction or other mixture problems.  These differences in air voids need to be considered and accounted for in any evaluation or analysis of the performance data.

The material test data that are available were further reviewed to evaluate other material and construction variations between and within the different cells of the experiment.  Figures 14 and 15 show the gradation test results for the percentage passing the number 4 and 200 sieves for the PATB material.  As illustrated, there are only a small percentage of the tests where the measured gradation may significantly restrict the layer’s capacity to remove any surface water infiltration quickly.  Figures 16 and 17 show other typical examples of the variability in the percentage passing the number 200 sieve for the HMA surface and ATB layers that exists in this SPS-1 experiment. 

This variability is typical for the other materials using standard construction practices for each specific material.  These test results suggest that the materials used in construction have similar physical properties.

TRAFFIC

Traffic data provide estimates of annual vehicle counts by vehicle classification and distribution of axle weights by axle type.  Annual traffic summary statistics are stored in the IMS traffic module, when available.  These data are supposed to be provided for each year after the roadway was opened to the traffic.  For the SPS-1 experiment, traffic data are collected at the project site using a combination of permanent and portable equipment by the individual States and Provinces.

The SPS-1 experiment design calls for continuous WIM monitoring, as permitted by WIM scale operating divisions.  Table TRF_MONITOR_BASIC_INFO was examined to identify the SPS-1 records with WIM, AVC data, and annual ESAL estimates.  The availability of WIM and AVC was further classified as “at least 1 day” or “continuous.”

 Table 9.  Summary of materials testing on the subgrade soils.

Project

Age, years

Subgrade Soil Testing—Percent Complete

Gradation

Atterberg Limits

Moist.-Den. Relations

Resilient Modulus

Permeability

Iowa

7.0

0

0

0

100

0

Alabama

6.4

100

100

100

100

0

Arizona

6.0

100

100

100

35

0

Kansas

5.8

0

100

100

50

0

Arkansas

5.7

100

100

100

0

0

Ohio

4.6

0

0

0

0

66

Nebraska

4.1

100

100

100

80

33

Michigan

4.0

35

35

35

85

0

Nevada

4.0

100

100

100

100

50

Florida

3.7

100

100

100

100

100

New Mexico

3.7

100

100

100

100

100

Virginia

3.7

100

100

100

0

100

Delaware

3.2

0

0

0

100

0

Texas

2.3

60

0

0

100

0

Oklahoma

2.1

100

35

0

100

0

Louisiana

2.1

100

60

100

100

0

Wisconsin

1.8

0

0

0

0

0

Montana

0.8

0

0

0

0

0

 Table 10.  Summary of materials testing on the unbound aggregate base materials.

Project

Age, years

Unbound Aggregate Base Testing—Percent Complete

Gradation

Atterberg Limits

Moist.-Den. Relations

Resilient Modulus

Permeability

Iowa

7.0

33

0

33

0

0

Alabama

6.4

100

0

67

0

0

Arizona

6.0

100

100

100

35

0

Kansas

5.8

0

0

0

0

0

Arkansas

5.7

0

0

0

0

0

Ohio

4.6

33

0

0

0

66

Nebraska

4.1

0

100

100

0

0

Michigan

4.0

66

66

66

0

0

Nevada

4.0

100

0

0

0

100

Florida

3.7

66

66

66

0

0

New Mexico

3.7

0

0

0

0

100

Virginia

3.7

100

100

0

0

0

Delaware

3.2

0

0

0

0

66

Texas

2.3

0

0

0

100

0

Oklahoma

2.1

0

0

0

0

0

Louisiana

2.1

0

0

0

33

0

Wisconsin

1.8

0

0

0

0

0

Montana

0.8

0

0

0

0

0


 Table 11.  Summary of materials testing on the permeable asphalt treated base mixtures.

Project

Age, years

Permeable Asphalt Treated Base Testing—
Percent Complete

Asphalt Content

Gradation

Iowa

7.0

100

100

Alabama

6.4

0

0

Arizona

6.0

100

100

Kansas

5.8

0

0

Arkansas

5.7

0

0

Ohio

4.6

100

100

Nebraska

4.1

67

100

Michigan

4.0

0

0

Nevada

4.0

0

0

Florida

3.7

33

33

New Mexico

3.7

33

33

Virginia

3.7

100

100

Delaware

3.2

66

66

Texas

2.3

0

0

Oklahoma

2.1

100

100

Louisiana

2.1

0

0

Wisconsin

1.8

0

0

Montana

0.8

0

0

 Table 12.  Summary of materials testing on the asphalt treated base mixtures.

Project

Age, years

HMA Testing—Percent Complete

Core Exam.

Spec. Grav. Bulk/Rice

Asphalt Content

Moisture Suscep.

Gradation

AC Viscosity

Iowa

7.0

67

0/0

100

0

100

50

Alabama

6.4

64

56/0

0

0

0

0

Arizona

6.0

100

100/100

100

100

100

100

Kansas

5.8

0

0/0

0

0

0

0

Arkansas

5.7

100

0/0

0

0

0

0

Ohio

4.6

0

0/33

33

0

33

17

Nebraska

4.1

100

33/100

100

0

33

35

Michigan

4.0

0

0/0

0

0

0

0

Nevada

4.0

75

5/0

0

0

0

0

Florida

3.7

100

100/100

100

100

100

100

New Mexico

3.7

100

100/100

100

100

100

100

Virginia

3.7

100

66/100

100

100

100

50

Delaware

3.2

56

33/66

66

0

66

0

Texas

2.3

0

0/0

0

0

0

0

Oklahoma

2.1

100

100/100

100

100

100

100

Louisiana

2.1

0

0/0

0

0

0

0

Wisconsin

1.8

0

0/0

0

0

0

0

Montana

0.8

0

0/0

0

0

0

0

Note:  LATB indirect tensile resilient modulus and strength tests are missing for all of the projects.

Table 13.  Summary of materials testing on the HMA mixtures.

Project

Age, years

HMA Testing—Percent Complete

Core Exam.

Spec. Grav. Bulk/Rice

Asphalt Content

Moisture Suscep.

Gradation

AC Viscosity

Iowa

7.0

0

0/67

0

0

0

0

Alabama

6.4

76

82/0

0

0

0

0

Arizona

6.0

100

100/100

100

0

100

75

Kansas

5.8

0

0/0

0

0

0

0

Arkansas

5.7

100

0/0

0

0

0

0

Ohio

4.6

86

35/100

100

0

100

75

Nebraska

4.1

50

30/100

33

0

33

18

Michigan

4.0

0

0/0

0

0

0

0

Nevada

4.0

100

50/0

0

0

0

0

Florida

3.7

94

100/100

100

100

100

100

New Mexico

3.7

100

100/100

100

100

100

100

Virginia

3.7

100

75

33

33

33

18

Delaware

3.2

81

86/0

100

0

100

100

Texas

2.3

0

0/0

0

0

0

0

Oklahoma

2.1

100

100/100

100

100

100

100

Louisiana

2.1

0

0/0

0

0

0

0

Wisconsin

1.8

0

0/0

0

0

0

0

Montana

0.8

0

0/0

0

0

0

0

Note:  HMA indirect tensile resilient modulus, strength, and creep compliance tests are missing for all of the projects.



 Table 14.  Summary of materials testing completed by material type for the core test sections, percent complete.

Climate

Subgrade Soil Classification

Project ID

Shoulder

Material

HMA Surface

Dense Graded Aggregate Base

Asphalt Treated Base

Permeable Asphalt Treated Base

Subgrade

Wet-Freeze

Fine-Grained

Iowa

HMA

6

11

56

100

14

Michigan

HMA

0

45

0

0

35

Ohio

HMA

82

17

19

100

9

Coarse-Grained

Delaware

HMA

75

12

25

67

14

Virginia

HMA

43

50

76

100

71

Wisconsin

HMA

0

0

0

0

0

Wet-No-Freeze

Fine-Grained

Alabama

HMA

10

40

8

0

86

Louisiana

HMA

0

6

0

0

71

Coarse-Grained

Arkansas

HMA

9

0

9

0

62

Florida

HMA

86

45

72

33

86

Dry-Freeze

Fine-Grained

Kansas

?

0

0

0

0

48

Nebraska

HMA

36

33

57

84

76

Coarse-Grained

Montana

HMA

0

0

0

0

0

Nevada

HMA

14

50

6

0

91

Dry-No-Freeze

Fine-Grained

New Mexico

HMA

86

33

90

33

100

Oklahoma

HMA

78

0

90

100

48

Texas

HMA

0

0

0

0

57

Coarse-Grained

Arizona

None

73

50

73

100

76

Note: The materials testing for the Wisconsin project is underway, but was not at Level E in the January 2000 release.

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Figure 11.  Histogram of air voids measured on the HMA surface layer.

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Figure 12.  Histogram of air voids measured on the HMA binder layer.

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Figure 13.  Histogram of air voids measured on the ATB layer.

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Figure 14.  Histogram of the material passing the number 4 sieve, PATB layer.

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Figure 15.  Histogram of material passing the number 200 sieve, PATB layer.

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Figure 16.  Histogram of material passing the number 200 sieve, HMA surface layer.


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Figure 17.  Histogram of material passing the number 200 sieve, ATB layer.

Continuous AVC and WIM monitoring were defined for two different conditions. In the past, LTPP has defined continuous AVC monitoring as over 300 AVC monitoring days in a given year and continuous WIM monitoring as over 210 WIM monitoring days in a given year.  However, based on variability measurements and the minimum number of sampling days being recommended from NCHRP Project 1-37A for sampling truck traffic, continuous AVC and WIM monitoring are defined as over 45 monitoring days in a given season.

 Table 8 provided a summary of the number of continuous WIM days available at each of the project sites.  Table 6 also identified those sites where WIM and AVC equipment had been installed.  As tabulated, over 50 percent of the SPS-1 projects do not have any WIM or AVC data at Level E in the IMS.  As previously stated, this is considered a significant detriment to achieving the experimental objectives and expectations.  On the positive side, WIM and AVC equipment have been installed at the Iowa, Ohio, Montana, Texas, and Wisconsin sites, but the data collected are not at Level E. Table 15 shows that the greatest amount of Level E traffic data, in general, are available for the oldest projects, as expected.

 In the original SPS-1 experimental design, traffic was incorporated as a covariant in the experimental design.  A traffic level of at least 100,000 ESALs per year was required for each of the projects.  The actual ESALs per year at each site are shown in table 8 (note that initial estimated ESALs are unavailable for six sites).  The traffic level requirement was met for all of the sites except the Texas project, which is located along a rural route with little truck traffic.  The project with the highest annual ESALs is the Florida project (1,463,000 per year).

 Table 15.  Summary of climatic and traffic data for the SPS-1 project sites.

Project

Age, years

Climate Data

Traffic Data

Equipment installed

Number of AWS days

Equipment installed

Number of WIM days

Number of AVC days

Iowa

7.0

check mark

815

check mark

108

Alabama

6.4

check mark

1,394

Arizona

6.0

check mark

1,480

check mark

1,588

1,544

Kansas

5.8

check mark

1,000

check mark

232

18

Arkansas

5.7

check mark

1,100

check mark

89

89

Ohio

4.6

check mark

1,600

check mark

Nebraska

4.1

check mark

1,024

check mark

531

581

Michigan

4.0

check mark

670

check mark

250

Nevada

4.0

check mark

check mark

338

299

Florida

3.7

check mark

800

check mark

342

220

New Mexico

3.7

check mark

1,075

Virginia

3.7

check mark

1,299

check mark

313

312

Delaware

3.2

check mark

1,200

Texas

2.3

check mark

187

check mark

Oklahoma

2.1

check mark

400

Louisiana

2.1

check mark

300

Wisconsin

1.8

check mark

check mark

Montana

0.8

check mark

370

check mark

 The range of traffic loadings between the sites will need to be fully considered in any comparative analysis of these data.  More importantly, the missing traffic data will severely restrict the use of the SPS-1 experiment data for validating mechanistic-empirical design and analysis methods.

MONITORING DATA

Several types of monitoring data are included in the LTPP IMS.  These monitoring data include distresses (from both manual and automated or PASCO surveys), longitudinal profiles, transverse profiles, deflection, and friction.  Chapter 3 of this report reviewed the required monitoring frequency for each of the data elements for the SPS-1 experiment. In general, these minimum requirements are being met for the long-term monitoring frequency, but have not been met for the initial data collection requirements.  The number of measurements for each of the test sections within each project was tabulated and discussed in appendix A.

Table 16 provides a summary of the minimum number of distress and other performance indicator measurements made at each of the SPS-1 project sites.  As tabulated, very few friction measurements have been performed on these projects, while there have been numerous deflection and manual distress surveys.  At least one survey for each of the monitoring data elements has been made at each site, with the exception of the friction surveys and transverse profile measurements at selected sites. 

Table 16.  Summary of the minimum number of distress and other performance indicator measurements  made at each project site.

Project

Region

Age, Years

Deflection Surveys

Distress

Transverse Profiles

Longitudinal Profiles

Friction Surveys

Manual

Pasco

Delaware

North Atlantic

3.2

1

3

0

2

7

0

Virginia

3.7

2

3

0

2

7

1

Iowa

North Central

7.0

3

1

2

4

6

5

Kansas

5.8

6

4

2

7

6

6

Nebraska

4.1

2

2

1

3

4

   0(1)

Michigan

4.0

2

4

1

2

3

1

Ohio

4.6

5

3

1

3

4

0

Wisconsin

1.8

1

1

0

   0(2)

3

0

Alabama

South

6.4

5

3

2

2

4

2

Arkansas

5.7

5

1

1

1

2

0

Florida

3.7

1

1

0

0

4

0

Louisiana

2.1

3

2

0

1

1

0

New Mexico

3.7

1

2

0

2

1

0

Oklahoma

2.1

2

3

0

0

1

0

Texas

2.3

1

3

0

2

2

0

Arizona

West

6.0

7

3

1

4

5

0

Montana

0.8

3

2

0

   0(3)

2

0

Nevada

4.0

6

3

1

3

3

0

Note:   

  1. Friction measurement are available for the Ohio project, but are not at Level E.
  2. Transverse profiles were measured on the Wisconsin project, but are not at Level E.
  3. Transverse profiles were performed in Montana at the same time that manual distress surveys were performed.  The two sets of transverse profile measurements are not included as Level E data in the IMS.

Transverse profiles are not yet measured at the Oklahoma and Florida sites.  Transverse profiles were measured for the Montana and Wisconsin projects, but those data are not yet at Level E and are unavailable in the IMS. The Wisconsin and Montana sites are relatively new, whereas the Oklahoma and Florida sites are over 2 years of age.

Longitudinal profiles have been completed at least once for all SPS-1 projects.  However, the first longitudinal profile measured on 9 of the 18 projects was more than 1 year after construction.  The discrepancy for the initial measurements may be related to the definition of the construction date or other scheduling difficulties as identified in chapter 3. In some cases, the construction date was defined as completion of pavement placement rather than acceptance by the State agency.  Those projects that were more than 1 year in age before the first longitudinal profile measurement was taken include Alabama, Arkansas, Florida, Iowa, Michigan, Nevada, New Mexico, Ohio, and Virginia.

Table 17 summarizes the age, in years, between each set of measurements for each performance indicator.  Most of the monitored data have been measured more frequently than required by the guidelines referenced in chapter 3.

Table 17.  Summary of the average time interval between the different performance indicator surveys.

Project

Age, years

Long. Profiles

Transverse Profiles

Distress

Deflection Surveys

Manual

Pasco

Iowa

7.0

1.2

1.8

7.0

3.5

2.3

Alabama

6.4

1.6

3.2

2.1

3.2

1.3

Arizona

6.0

1.2

1.5

2.0

6.0

0.9

Kansas

5.8

1.0

0.8

1.5

2.9

1.0

Arkansas

5.7

2.9

5.7

5.7

5.7

1.3

Ohio

4.6

1.2

1.5

1.5

4.6

0.9

Nebraska

4.1

1.0

1.4

2.1

4.1

2.1

Michigan

4.0

1.3

2.0

1.0

4.0

2.0

Nevada

4.0

1.3

1.3

1.3

4.0

0.7

Florida

3.7

0.9

3.7

3.7

New Mexico

3.7

3.7

1.9

1.9

3.7

Virginia

3.7

0.5

1.9

1.2

1.9

Delaware

3.2

0.5

1.6

1.1

3.2

Texas

2.3

1.2

1.2

0.8

2.3

Oklahoma

2.1

2.1

0.7

1.1

Louisiana

2.1

2.1

2.1

1.1

0.7

Wisconsin

1.8

0.6

1.8

1.8

Montana

0.8

0.4

0.4

0.3


DYNAMIC LOAD RESPONSE DATA

Various flexible pavement test sections of the Ohio SPS-1 site were selected for measuring pavement response under controlled loading conditions.  The instrumented sections are: 329-0102, 39-0104, 39-0108, and 39-0110. During the early life of the pavement, dynamic load response data were collected on a quarterly basis.  However, data collection was terminated after 2 years.
The dynamic load response data for the flexible pavement test sections are stored in the DLR_* module in the following nine IMS tables:

The data availability assessment of these tables is provided in table 18.  All records in these tables are at Level E.

Table 18.  Summary of Level E dynamic load response data for the Ohio SPS-1 project.

Data Table Name

Total Records (All at E)

Records for Each Section

0102

0104

0108

0110

DLR_LVDT_CONFIG_AC

131

16

34

40

41

DLR_LVDT_TRACE_SUM_AC

348

74

96

98

80

DLR_MASTER_AC

23

4

7

6

6

DLR_PRESSURE_CONFIG_AC

52

8

16

14

14

DLR_PRESSURE_TRACE_SUM_AC

335

71

121

79

64

DLR_STRAIN_CONFIG_AC

571

72

192

147

160

DLR_STRAIN_TRACE_SUM_AC

304

18

86

88

112

dlr_test_matrix

350

48

111

92

99

DLR_TRUCK_GEOMETRY

1

1 Truck ID/Type

SUMMARY

 Table 19 presents an overall summary of the SPS-1 projects, identifying the project deviations, construction difficulties, and overall data completeness.  These factors have been aggregated into an “adequacy code,” which consists of a numerical scale from 0 to 5 and provides an overall rating of the project and test sections for fulfilling the original experimental objectives and expectations.  A definition of this numerical scale is given below.

0 = The project will be unable to meet the experimental objectives and expectations or the project has been recently constructed and has only limited data at this time.
1 = The project has major limitations in the data.  There are significant data deficiencies/missing data that will have a significant detrimental impact on meeting the experimental objectives and expectations.
2 = The project has missing data that will have an impact on the reliability of the results for achieving the experimental objectives and expectations.
3 = The project has some missing data and deficiencies.  However, assumptions combined with the existing data can be used to meet the experimental objectives and expectations.
4 = The project has minor limitations, missing data, or data deficiencies that will have little impact on meeting the experimental objectives and expectations.
5 = The project has adequate data to meet the experimental objectives and expectations.

Relatively few project deviations and problems were encountered during the construction of these projects. Of those difficulties and deviations noted, none are considered fatal to the overall expectations of the projects included in this experiment.  However, some data elements at specific project sites will have a negative effect on accomplishing the experimental objectives if they are not collected in the future.  Primarily, these include traffic data and some of the materials/layer properties. The omission of these data elements is reflected in the overall adequacy code for each project.

 As listed in table 19, two projects have an adequacy code of 0.  The Montana and Wisconsin projects are newly constructed and have little data in the database at this time. It is expected that the adequacy of these two projects will increase as more data become available and are entered into the IMS. 

Three projects have an adequacy code of 2: Alabama, Louisiana, and Oklahoma.  None of these projects have WIM equipment installed at the site; all have substantial materials test data that are missing; and most have missing or infrequent monitoring data.

Six of the projects were assigned an adequacy code of 3 for a variety of reasons.  These projects include Arkansas, Delaware, Florida, Michigan, New Mexico, and Texas.  The traffic data and a substantial amount of materials test data are unavailable for most of these projects.  The adequacy code of these projects will increase as the data reach Level E.

Table 19.    Summary of the overall construction difficulties and deviations, and the adequacy code for the projects included in the SPS-1 experiment.

Project

Construction Difficulties and Deviations

Adequacy Code

Alabama

  • Mechanical problem with paver; construction joint placed in Section 010111.
  • Deformations occurred on top of the PATB.
  • DGAB contained excess minus 200 material.

2

Arizona

  • Rain delays during subgrade preparation.
  • Fill material pumped, but was replaced prior to paving.
  • Section 0122 included a layer of DGAB below the PATB.
  • DGAB for sections 0119 and 0122 did not meet the gradation requirements.

5

Arkansas

  • Rain caused construction delays, but surfaces were allowed to dry prior to resuming construction.
  • DGAB thickness on section 0114 was less than half of the required value.  Many other sections were also less than the design value.
  • The stability of the HMA mixture was less than the specified value.

3

Delaware

  • High water table along the project.
  • Ditches were shallow, so outlets of edge drains were not placed at the 76-m spacing.
  • The number 4 sieve from the gradation tests for the HMA surface did not meet the project specifications.

3

Florida

  • Rain delays caused the DGAB to be reworked multiple times.
  • The number 4 sieve from the gradation tests for the HMA surface and binder layers did not meet the project specification.

3

Iowa

  • Multiple rain delays, but surfaces were allowed to dry and were reworked.
  • PATB “rolled out” on the sides, which resulted in the placement of an extra lift to meet the thickness requirement.
  • The number 4 sieve from the gradation tests for the HMA binder layer exceeded the project requirements.

4

Kansas

  • Excessive moisture in the subbase, which caused difficulty in compacting the material.
  • Fly ash was added to the subbase layer for stabilization purposes.

4

Louisiana

  • Test sections for thickness cells 1 to 12 rather than 13 to 24 were built.
  • Rain delays.
  • Subgrade was stabilized with cement.
  • Fabric did not meet overlay requirements.
  • Aggregate in drainage trenches contained fines.
  • DGAB was compacted in one lift.
  • Select material was used at site to achieve the final elevation.

2

Michigan

  • No construction report was available for review.

3

Montana

 

  • Recently constructed.

0

Nebraska

 

  • Three test sections were constructed over culverts.
  • Rain delays.
  • The minus 200 material for the PATB exceeded the project requirements.

4

Nevada

  • Plant breakdown occurred while placing the PATB for test section 320110.
  • The DGAB contained excess minus 200 materials.

4

New Mexico

  • HMA facility breakdown.
  • High air voids reported in the ATB prior to plant breakdown.
  • Localized tenderness problem noted.

3

Ohio

  • Fill material placed on all sections.
  • DGAB thickness was much larger than the planned thickness.
  • The number 4 sieve for the HMA surface did not meet the project requirements.

4

Oklahoma

  • The number 4 sieve for the HMA surface did not meet the project requirements.
  • One of the two ATB lifts exceeded the project thickness requirements.

2

Texas

  • Transverse interceptor drains not installed along the project.

3

Virginia

 

  • Subgrade treated with cement.
  • The number 4 sieve for the HMA surface did not meet the project requirements.

4

Wisconsin

 

  • Recently constructed.

0


 The Michigan project has an adequacy code of 3 rather than 4 because four of the test sections were taken out of service without measurements for distress, longitudinal profile, international roughness index (IRI), or transverse profile (rut depth).  These deficiencies should have minimal impact on the SPS-1 experiment because the project is in the wet-freeze climate and fine-grained subgrade soil site factorial cell of the experiment (refer to table 3), and there are three other projects within this cell that will provide sufficient data for analysis purposes.   In addition, the value of this project will increase after the test results reach a Level E status.  All other projects were assigned an adequacy code of 4 or 5.

 


The Federal Highway Administration (FHWA) is a part of the U.S. Department of Transportation and is headquartered in Washington, D.C., with field offices across the United States. is a major agency of the U.S. Department of Transportation (DOT).
The Federal Highway Administration (FHWA) is a part of the U.S. Department of Transportation and is headquartered in Washington, D.C., with field offices across the United States. is a major agency of the U.S. Department of Transportation (DOT). Provide leadership and technology for the delivery of long life pavements that meet our customers needs and are safe, cost effective, and can be effectively maintained. Federal Highway Administration's (FHWA) R&T Web site portal, which provides access to or information about the Agency’s R&T program, projects, partnerships, publications, and results.
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United States Department of Transportation - Federal Highway Administration